1. Field of the Invention
As disclosed herein, data is extracted from handwritten information when the information is captured as sequences of strokes, vectors, or marks by storing temporal data within the color or gray-scale encoding of pixel values within a bitmapped image. More particularly, a system and method is provided which relates to such information representing responses to assessment items such as described in the nonprovisional patent application by Roger P. Creamer, et al. (Creamer), Ser. No. 10/701,434, which is incorporated herein by reference. The system and method, however, can be advantageously used to extract data from or to improve the presentation of information from electronic representation of temporal human marks including surveys, questionnaires, applications, and the like. Additionally, the system and method can be advantageously used to store other types of data within a bitmapped image.
2. Background Art
As disclosed by Creamer, there are many suitable devices that can be utilized to capture the strokes, vectors, or marks of pencils, pens, stylus, or similar marking instruments as the strokes, vectors, or marks are made by the respondent. Creamer describes a system and method to capture and process handwritten responses to assessment items by human respondents. They disclose how to first present a stimulus to the respondent, such as a test item. They additionally disclose methods and apparatus to obtain an electronic representation of the respondent's handwritten response to the stimulus.
As acknowledged by Creamer, it is often difficult to determine the intended response of a respondent when looking at the response on paper or when looking at a reconstructed image of the response because the respondent can make changes over time. As noted by Creamer, this is true both for selected responses and constructed responses. For a selected response, the respondent makes a mark to select one of a number of options such as with multiple choice items. For a constructed response, the respondent writes or draws or otherwise creates a response to a stimulus such that the response can subsequently be evaluated either by a teacher or evaluator or by a two-step process including conversion to text followed by an automated text evaluation.
While Creamer identifies several different types of apparatus that can be used to capture an electronic representation of the respondent's handwriting, most existing systems merely combine all of the marks into a reconstituted image of the total response. This reconstituted image is appropriate for determining a respondent's intended response when the response is unambiguous. When there are crossed out materials, multiple marks, or other corrections and changes made by the respondent, determining the respondent's intent from the reconstituted response suffers from the same problems as when determining the respondent's intent from paper.
Creamer correctly indicates that the respondent's intent can be more likely properly understood by utilizing the temporal sequence of marks: for example, when more than one answer is marked in a multiple-choice item, the last answer marked can be treated as the intended answer. For constructed response, a respondent's intent may be better determined if some marks are eliminated, such as marks made early on and marks made to cross off earlier mistakes. A system and method is disclosed herein to advantageously utilize both the temporal data and the mark information for determining the respondent's intended response by both automated and human evaluation.
Generally, images containing respondent information are processed by systems designed to extract data from the image representing the marks made by the respondent. A well-known example is “key-from-image” in which a human operator enters data, typically using a keyboard, based on the viewed image. As shown in U.S. Pat. No. 5,672,060 (Poor), constructed responses are often scored by having evaluators or readers view the image of the constructed response on a display and then enter an appropriate score or grade for the student's response. For selected or multiple-choice responses, “image-to-OMR” systems have been developed such as shown by Poor in pending U.S. application 60/224,327 filed Aug. 11, 2000, the disclosure of which is hereby incorporated by reference. Additionally, character recognition systems can be used to convert handwritten characters to text. Examples include the Nestor System from NCS/Pearson, “Eyes and Hands”, and “Isirus” by Hewlett-Packard. All of these systems are based on processing traditional bitmapped images.
Traditionally, electronic images can be stored in two different modes: vector representation and bitmapped representation.
In vector representation, the total image is depicted as a series of shapes. These shapes may be lines, circles, dots, or other shapes. When presented together, they depict the entire image. In the current case, each electronic mark can be saved as a separate vector, so that the sequence of vectors in the image may correspond to the temporal sequence of marks made by the respondent. While vector representation can contain the temporal sequence by the sequence of vectors, images stored as vectors tend to be larger than images stored as bitmapped images and tend to require significantly more processing time to display or otherwise process.
In bitmapped images, the total image consists of a matrix of pixels or dots. For the current case, each mark made by a respondent represents one or more pixels. A total image can therefore be created by setting such pixels to represent a mark. The inherent weakness of this traditional process is that when marks overlap, it does not provide a mechanism to identify each individual mark or to determine the sequence of the marks.
One aspect of the system and method disclosed herein is to provide solutions on how to electronically store a single bitmapped image of a response while maintaining sufficient temporal data to accurately determine the intent of the respondent when the traditional total image is insufficient. An additional aspect of the system and method disclosed herein is to create derivative images from the single bitmapped image suitable for existing data extraction techniques including, but not limited to key-from-image, human evaluation or scoring, character recognition, conversion to text, and scoring of selected responses.